{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 110,
   "id": "7de19eeb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "id": "927cb437",
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('./train_X.pkl' , \"rb\" ) as file :\n",
    "    train_X = pickle.load(file)\n",
    "with open('./train_y.pkl' , \"rb\" ) as file :\n",
    "    train_y = pickle.load(file)\n",
    "with open('./test_X.pkl' , \"rb\" ) as file :\n",
    "    test_X = pickle.load(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "9364abb8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# lgb、catboost、xgb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "6b378cb1",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "import time\n",
    "import gc\n",
    "import matplotlib.pyplot as plt\n",
    "import pickle\n",
    "import lightgbm as lgb\n",
    "from sklearn.model_selection import StratifiedKFold, KFold\n",
    "from sklearn.metrics import roc_auc_score,f1_score\n",
    "from sklearn.decomposition import TruncatedSVD\n",
    "from sklearn.feature_extraction.text import CountVectorizer, TfidfVectorizer\n",
    "from sklearn.preprocessing import LabelEncoder,OneHotEncoder\n",
    "from scipy import sparse\n",
    "import seaborn as sns\n",
    "from datetime import *\n",
    "from functools import reduce\n",
    "from sklearn.metrics import roc_curve\n",
    "from sklearn.model_selection import StratifiedKFold\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn import feature_selection\n",
    "import datetime\n",
    "import xgboost as xgb\n",
    "from sklearn.feature_selection import VarianceThreshold\n",
    "from catboost import CatBoostClassifier as cb\n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "import optuna\n",
    "from sklearn.metrics import precision_score, recall_score,f1_score\n",
    "from lightgbm import *\n",
    "seed_list=[1993,2008,4096,1015]\n",
    "import random\n",
    "random.seed(5354)\n",
    "os.environ['PYTHONHASHSEED'] = str(5354)\n",
    "np.random.seed(5354)\n",
    "pd.set_option('display.max_info_columns', 500)\n",
    "pd.set_option('display.max_columns', 1000)\n",
    "pd.set_option('display.max_row', 300)\n",
    "pd.set_option('display.float_format', lambda x: ' %.5f' % x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "id": "393614b5",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.utils.class_weight import compute_class_weight"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "id": "78c3006d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def cv_model(clf, train_x, train_y, test_x, clf_name, seed=None, n_classes=None):\n",
    "    folds = 5\n",
    "    kf = StratifiedKFold(n_splits=folds, shuffle=True, random_state=seed)\n",
    "    \n",
    "    # 初始化oof和predict为二维数组（多分类）\n",
    "    oof = np.zeros((train_x.shape[0], n_classes))\n",
    "    predict = np.zeros((test_x.shape[0], n_classes))\n",
    "    df_feature_importance = pd.DataFrame()\n",
    "    cv_scores = []\n",
    "    \n",
    "    # 类别列处理\n",
    "    cols_list = train_x.columns.tolist()\n",
    "    cats_list = train_x.select_dtypes(include='category').columns\n",
    "    cats_list_idx = [i for i in range(len(cols_list)) if cols_list[i] in cats_list]\n",
    "    \n",
    "    # 类别编码处理\n",
    "    if clf_name in [\"xgb\", \"cat\"]:\n",
    "        for c in cats_list:\n",
    "            le = LabelEncoder()\n",
    "            train_x[c] = train_x[c].astype('str')\n",
    "            test_x[c] = test_x[c].astype('str')\n",
    "            lb_data = pd.concat([train_x[c], test_x[c]], axis=0)\n",
    "            le.fit(lb_data)\n",
    "            train_x[c] = le.transform(train_x[c])\n",
    "            test_x[c] = le.transform(test_x[c])\n",
    "    \n",
    "    # 处理无穷值\n",
    "    if clf_name == \"xgb\":\n",
    "        train_x.replace(np.inf, 9999999, inplace=True)\n",
    "        train_x.replace(-np.inf, -9999999, inplace=True)\n",
    "        test_x.replace(np.inf, 9999999, inplace=True)\n",
    "        test_x.replace(-np.inf, -9999999, inplace=True)\n",
    "    \n",
    "    for i, (train_index, valid_index) in enumerate(kf.split(train_x, train_y)):\n",
    "        print('************************************ {} ************************************'.format(str(i+1)))\n",
    "        trn_x, trn_y, val_x, val_y = train_x.iloc[train_index], train_y[train_index], train_x.iloc[valid_index], train_y[valid_index]\n",
    "\n",
    "        if clf_name == \"lgb\":\n",
    "            # 多分类参数设置 - 添加is_unbalance=True实现class_weight='balanced'\n",
    "            params = {\n",
    "                'boost_from_average': 'false',\n",
    "                'boost': 'gbdt',\n",
    "                'metric': 'multi_logloss',\n",
    "                'num_class': n_classes,\n",
    "                'max_depth': 7,\n",
    "                'num_leaves': 2**7 - 1,\n",
    "                'objective': 'multiclass',\n",
    "                'min_child_weight': 16,\n",
    "                'min_data_in_leaf': 6,\n",
    "                'min_split_gain': 0.7,\n",
    "                'bagging_fraction': 0.82,\n",
    "                'feature_fraction': 0.74,\n",
    "                'reg_lambda': 2.65,\n",
    "                'reg_alpha': 3.85,\n",
    "                'bagging_freq': 1,\n",
    "                'seed': seed,\n",
    "                'nthread': 8,\n",
    "                'n_jobs': 8,\n",
    "                'verbose': -1,\n",
    "                'is_unbalance': True  # 添加class_weight='balanced'等效参数\n",
    "            }\n",
    "            \n",
    "            train_matrix = clf.Dataset(trn_x, label=trn_y)\n",
    "            valid_matrix = clf.Dataset(val_x, label=val_y)\n",
    "            callbacks = [log_evaluation(period=100), early_stopping(stopping_rounds=500)]\n",
    "            \n",
    "            model = clf.train(params, train_matrix, num_boost_round=20000, \n",
    "                             valid_sets=[train_matrix, valid_matrix], \n",
    "                             callbacks=callbacks)\n",
    "            \n",
    "            val_pred = model.predict(val_x, num_iteration=model.best_iteration)\n",
    "            test_pred = model.predict(test_x, num_iteration=model.best_iteration)\n",
    "            \n",
    "            # 特征重要性\n",
    "            df_fold_importance = pd.DataFrame()\n",
    "            df_fold_importance['feature'] = train_x.columns\n",
    "            df_fold_importance['importance'] = model.feature_importance()\n",
    "            df_fold_importance['fold'] = i + 1\n",
    "            df_feature_importance = pd.concat([df_feature_importance, df_fold_importance], axis=0)\n",
    "\n",
    "        elif clf_name == \"xgb\":\n",
    "            # 计算样本权重实现class_weight='balanced'\n",
    "            class_weights = compute_class_weight('balanced', classes=np.unique(trn_y), y=trn_y)\n",
    "            sample_weights = np.array([class_weights[i] for i in trn_y])\n",
    "            \n",
    "            # 多分类参数设置\n",
    "            params = {\n",
    "                'booster': 'gbtree',\n",
    "                'objective': 'multi:softprob',\n",
    "                'eval_metric': 'mlogloss',\n",
    "                'num_class': n_classes,\n",
    "                'gamma': 1,\n",
    "                'min_child_weight': 1.5,\n",
    "                'max_depth': 7,\n",
    "                'lambda': 10,\n",
    "                'subsample': 0.7,\n",
    "                'colsample_bytree': 0.7,\n",
    "                'colsample_bylevel': 0.7,\n",
    "                'eta': 0.05,\n",
    "                'tree_method': 'exact',\n",
    "                'seed': seed,\n",
    "                'nthread': 8\n",
    "            }\n",
    "            \n",
    "            train_matrix = clf.DMatrix(trn_x, label=trn_y, weight=sample_weights)  # 添加样本权重\n",
    "            valid_matrix = clf.DMatrix(val_x, label=val_y)\n",
    "            test_matrix = clf.DMatrix(test_x)\n",
    "            \n",
    "            watchlist = [(train_matrix, 'train'), (valid_matrix, 'eval')]\n",
    "            \n",
    "            model = clf.train(params, train_matrix, num_boost_round=20000, \n",
    "                             evals=watchlist, verbose_eval=100, \n",
    "                             early_stopping_rounds=500)\n",
    "            \n",
    "            val_pred = model.predict(valid_matrix)\n",
    "            test_pred = model.predict(test_matrix)\n",
    "            \n",
    "            # 特征重要性\n",
    "            df_fold_importance = pd.DataFrame()\n",
    "            scores = model.get_score(importance_type='gain')\n",
    "            if scores:\n",
    "                df_fold_importance['feature'] = scores.keys()\n",
    "                df_fold_importance['importance'] = scores.values()\n",
    "                df_fold_importance['fold'] = i + 1\n",
    "                df_feature_importance = pd.concat([df_feature_importance, df_fold_importance], axis=0)\n",
    "\n",
    "        elif clf_name == \"cat\":\n",
    "            # 多分类参数设置 - 添加auto_class_weights='Balanced'\n",
    "            model = clf(\n",
    "                iterations=10000,\n",
    "                random_seed=seed,\n",
    "                loss_function='MultiClass',\n",
    "                eval_metric='MultiClass',\n",
    "                learning_rate=0.01,\n",
    "                max_depth=5,\n",
    "                early_stopping_rounds=200,\n",
    "                metric_period=100,\n",
    "                l2_leaf_reg=3,\n",
    "                task_type='CPU',\n",
    "                auto_class_weights='Balanced'  # 添加class_weight='balanced'\n",
    "            )\n",
    "            \n",
    "            model.fit(trn_x, trn_y, eval_set=(val_x, val_y),\n",
    "                      use_best_model=True, cat_features=cats_list_idx,\n",
    "                      verbose=1)\n",
    "            \n",
    "            val_pred = model.predict_proba(val_x)\n",
    "            test_pred = model.predict_proba(test_x)\n",
    "            \n",
    "            # 特征重要性\n",
    "            df_fold_importance = pd.DataFrame()\n",
    "            df_fold_importance['feature'] = train_x.columns\n",
    "            df_fold_importance['importance'] = model.feature_importances_\n",
    "            df_fold_importance['fold'] = i + 1\n",
    "            df_feature_importance = pd.concat([df_feature_importance, df_fold_importance], axis=0)\n",
    "        \n",
    "        # 存储预测概率\n",
    "        oof[valid_index] = val_pred\n",
    "        predict += test_pred / folds\n",
    "        \n",
    "        # 计算macro F1\n",
    "        val_pred_labels = np.argmax(val_pred, axis=1)\n",
    "        fold_f1 = f1_score(val_y, val_pred_labels, average='macro')\n",
    "        cv_scores.append(fold_f1)\n",
    "        print('Macro F1 CV score: {:<8.5f}'.format(fold_f1))\n",
    "    \n",
    "    mean_cv_f1 = np.mean(cv_scores)\n",
    "    print(\"平均 Macro F1:::\", mean_cv_f1)\n",
    "    return oof, predict, model, df_feature_importance, mean_cv_f1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "id": "3396cf40",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "************************************ 1 ************************************\n",
      "Training until validation scores don't improve for 500 rounds\n",
      "[100]\ttraining's multi_logloss: 0.730389\tvalid_1's multi_logloss: 0.827841\n",
      "[200]\ttraining's multi_logloss: 0.721765\tvalid_1's multi_logloss: 0.828297\n",
      "[300]\ttraining's multi_logloss: 0.716535\tvalid_1's multi_logloss: 0.829015\n",
      "[400]\ttraining's multi_logloss: 0.713452\tvalid_1's multi_logloss: 0.830121\n",
      "[500]\ttraining's multi_logloss: 0.711041\tvalid_1's multi_logloss: 0.83067\n",
      "Early stopping, best iteration is:\n",
      "[97]\ttraining's multi_logloss: 0.731325\tvalid_1's multi_logloss: 0.827522\n",
      "Macro F1 CV score: 0.32511 \n",
      "************************************ 2 ************************************\n",
      "Training until validation scores don't improve for 500 rounds\n",
      "[100]\ttraining's multi_logloss: 0.7343\tvalid_1's multi_logloss: 0.813113\n",
      "[200]\ttraining's multi_logloss: 0.724872\tvalid_1's multi_logloss: 0.810863\n",
      "[300]\ttraining's multi_logloss: 0.720391\tvalid_1's multi_logloss: 0.81058\n",
      "[400]\ttraining's multi_logloss: 0.717736\tvalid_1's multi_logloss: 0.809958\n",
      "[500]\ttraining's multi_logloss: 0.714856\tvalid_1's multi_logloss: 0.811529\n",
      "[600]\ttraining's multi_logloss: 0.713136\tvalid_1's multi_logloss: 0.812101\n",
      "[700]\ttraining's multi_logloss: 0.711489\tvalid_1's multi_logloss: 0.811742\n",
      "Early stopping, best iteration is:\n",
      "[251]\ttraining's multi_logloss: 0.721915\tvalid_1's multi_logloss: 0.809852\n",
      "Macro F1 CV score: 0.34064 \n",
      "************************************ 3 ************************************\n",
      "Training until validation scores don't improve for 500 rounds\n",
      "[100]\ttraining's multi_logloss: 0.73013\tvalid_1's multi_logloss: 0.815313\n",
      "[200]\ttraining's multi_logloss: 0.720964\tvalid_1's multi_logloss: 0.813965\n",
      "[300]\ttraining's multi_logloss: 0.716145\tvalid_1's multi_logloss: 0.813842\n",
      "[400]\ttraining's multi_logloss: 0.713156\tvalid_1's multi_logloss: 0.813274\n",
      "[500]\ttraining's multi_logloss: 0.710527\tvalid_1's multi_logloss: 0.815267\n",
      "[600]\ttraining's multi_logloss: 0.709315\tvalid_1's multi_logloss: 0.814988\n",
      "[700]\ttraining's multi_logloss: 0.70798\tvalid_1's multi_logloss: 0.816102\n",
      "[800]\ttraining's multi_logloss: 0.706756\tvalid_1's multi_logloss: 0.816579\n",
      "Early stopping, best iteration is:\n",
      "[319]\ttraining's multi_logloss: 0.715617\tvalid_1's multi_logloss: 0.81302\n",
      "Macro F1 CV score: 0.38860 \n",
      "************************************ 4 ************************************\n",
      "Training until validation scores don't improve for 500 rounds\n",
      "[100]\ttraining's multi_logloss: 0.733902\tvalid_1's multi_logloss: 0.812871\n",
      "[200]\ttraining's multi_logloss: 0.723468\tvalid_1's multi_logloss: 0.812939\n",
      "[300]\ttraining's multi_logloss: 0.71933\tvalid_1's multi_logloss: 0.81374\n",
      "[400]\ttraining's multi_logloss: 0.716545\tvalid_1's multi_logloss: 0.81559\n",
      "[500]\ttraining's multi_logloss: 0.713762\tvalid_1's multi_logloss: 0.817913\n",
      "[600]\ttraining's multi_logloss: 0.711536\tvalid_1's multi_logloss: 0.818037\n",
      "Early stopping, best iteration is:\n",
      "[114]\ttraining's multi_logloss: 0.732077\tvalid_1's multi_logloss: 0.812256\n",
      "Macro F1 CV score: 0.39354 \n",
      "************************************ 5 ************************************\n",
      "Training until validation scores don't improve for 500 rounds\n",
      "[100]\ttraining's multi_logloss: 0.724389\tvalid_1's multi_logloss: 0.819249\n",
      "[200]\ttraining's multi_logloss: 0.715885\tvalid_1's multi_logloss: 0.820947\n",
      "[300]\ttraining's multi_logloss: 0.711241\tvalid_1's multi_logloss: 0.821843\n",
      "[400]\ttraining's multi_logloss: 0.707819\tvalid_1's multi_logloss: 0.822888\n",
      "[500]\ttraining's multi_logloss: 0.70537\tvalid_1's multi_logloss: 0.823341\n",
      "Early stopping, best iteration is:\n",
      "[52]\ttraining's multi_logloss: 0.739236\tvalid_1's multi_logloss: 0.817633\n",
      "Macro F1 CV score: 0.32712 \n",
      "平均 Macro F1::: 0.35500066866972013\n"
     ]
    }
   ],
   "source": [
    "# 假设原始标签是1-4\n",
    "n_classes = 4\n",
    "\n",
    "# 转换标签为0-3\n",
    "train_y_converted = train_y - 1\n",
    "\n",
    "# 调用函数\n",
    "oof_probs, test_probs, model, feat_importance, mean_f1 = cv_model(\n",
    "    lgb, train_X, train_y_converted, test_X, \"lgb\", seed=42, n_classes=n_classes\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "id": "f5985a23",
   "metadata": {},
   "outputs": [],
   "source": [
    "# # 假设原始标签是1-4\n",
    "# n_classes = 4\n",
    "\n",
    "# # 转换标签为0-3\n",
    "# train_y_converted = train_y - 1\n",
    "\n",
    "# # 调用函数\n",
    "# oof_probs, test_probs, model, feat_importance, mean_f1 = cv_model(\n",
    "#     xgb, train_X, train_y_converted, test_X, \"xgb\", seed=42, n_classes=n_classes\n",
    "# )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "id": "1b5dae02",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "默认阈值Macro F1: 0.35626\n",
      "最优阈值: [1.1058088  0.9726679  0.66576777 1.44673543]\n",
      "最优阈值Macro F1: 0.39703\n"
     ]
    }
   ],
   "source": [
    "# 1. 默认阈值预测（直接取最大概率）\n",
    "default_preds_converted = np.argmax(oof_probs, axis=1)\n",
    "default_preds = default_preds_converted + 1  # 转换回1-4范围\n",
    "default_f1 = f1_score(train_y, default_preds, average='macro')\n",
    "print(f\"默认阈值Macro F1: {default_f1:.5f}\")\n",
    "\n",
    "# 2. 最优阈值预测（通过优化）\n",
    "from sklearn.preprocessing import label_binarize\n",
    "from scipy.optimize import minimize\n",
    "\n",
    "# 优化函数\n",
    "def optimize_thresholds(thresholds):\n",
    "    adjusted_probs = oof_probs / thresholds\n",
    "    preds = np.argmax(adjusted_probs, axis=1)\n",
    "    return -f1_score(train_y_converted, preds, average='macro')\n",
    "\n",
    "# 优化阈值\n",
    "result = minimize(optimize_thresholds, np.ones(n_classes), \n",
    "                  method='Nelder-Mead', \n",
    "                  bounds=[(0.1, 10)] * n_classes)\n",
    "\n",
    "best_thresholds = result.x\n",
    "print(\"最优阈值:\", best_thresholds)\n",
    "\n",
    "# 应用最优阈值\n",
    "adjusted_probs = oof_probs / best_thresholds\n",
    "best_preds_converted = np.argmax(adjusted_probs, axis=1)\n",
    "best_preds = best_preds_converted + 1  # 转换回1-4范围\n",
    "best_f1 = f1_score(train_y, best_preds, average='macro')\n",
    "print(f\"最优阈值Macro F1: {best_f1:.5f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "id": "d27f4f13",
   "metadata": {},
   "outputs": [],
   "source": [
    "# 测试集预测\n",
    "# 默认阈值预测\n",
    "test_preds_default_converted = np.argmax(test_probs, axis=1)\n",
    "test_preds_default = test_preds_default_converted + 1\n",
    "\n",
    "# 最优阈值预测\n",
    "adjusted_test_probs = test_probs / best_thresholds\n",
    "test_preds_optimized_converted = np.argmax(adjusted_test_probs, axis=1)\n",
    "test_preds_optimized = test_preds_optimized_converted + 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "id": "d2331bc9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "默认阈值预测分布:\n",
      "4    19328\n",
      "2     3686\n",
      "1      699\n",
      "3      143\n",
      "Name: 默认预测, dtype: int64\n",
      "\n",
      "最优阈值预测分布:\n",
      "4    16726\n",
      "2     3654\n",
      "3     3010\n",
      "1      466\n",
      "Name: 优化预测, dtype: int64\n"
     ]
    }
   ],
   "source": [
    "# 保存结果\n",
    "results = pd.DataFrame()\n",
    "results['默认预测'] = test_preds_default\n",
    "results['优化预测'] = test_preds_optimized\n",
    "\n",
    "# 输出两种结果的分布\n",
    "print(\"\\n默认阈值预测分布:\")\n",
    "print(results['默认预测'].value_counts())\n",
    "\n",
    "print(\"\\n最优阈值预测分布:\")\n",
    "print(results['优化预测'].value_counts())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "e55cb321",
   "metadata": {},
   "outputs": [],
   "source": [
    "submission = pd.read_csv(\"./test.csv\")[['Id']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "id": "8f0722d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "submission['Target'] = results['默认预测']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "1b7c649a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "# 获取当前时间并格式化为月日时分秒\n",
    "current_time = datetime.now().strftime(\"%m%d_%H%M%S\")\n",
    "\n",
    "# 在文件名中添加时间信息\n",
    "filename = f'submission_{current_time}_default.csv'\n",
    "submission.to_csv(filename, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "ce5c2339",
   "metadata": {},
   "outputs": [],
   "source": [
    "submission['Target'] = results['优化预测']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "id": "5c5169f2",
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import datetime\n",
    "\n",
    "# 获取当前时间并格式化为月日时分秒\n",
    "current_time = datetime.now().strftime(\"%m%d_%H%M%S\")\n",
    "\n",
    "# 在文件名中添加时间信息\n",
    "filename = f'submission_{current_time}_best.csv'\n",
    "submission.to_csv(filename, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "799a6d73",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "def plot_feature_importance(df_feature_importance, top_n=20, figsize=(12, 10)):\n",
    "    \"\"\"\n",
    "    绘制特征重要性水平条形图\n",
    "    \n",
    "    参数:\n",
    "    df_feature_importance: 包含特征重要性数据的DataFrame\n",
    "    top_n: 显示前N个最重要的特征（默认20）\n",
    "    figsize: 图表尺寸（默认12x10）\n",
    "    \"\"\"\n",
    "    # 计算每个特征的平均重要性\n",
    "    mean_importance = df_feature_importance.groupby('feature')['importance'].mean().reset_index()\n",
    "    \n",
    "    # 按重要性排序并选择最重要的top_n个特征\n",
    "    mean_importance = mean_importance.sort_values('importance', ascending=False).tail(top_n)\n",
    "    \n",
    "    # 创建图表\n",
    "    plt.figure(figsize=figsize)\n",
    "    ax = sns.barplot(\n",
    "        x='importance',\n",
    "        y='feature',\n",
    "        data=mean_importance,\n",
    "        palette='viridis',\n",
    "        orient='h'\n",
    "    )\n",
    "    \n",
    "    # 添加标题和标签\n",
    "    plt.title(f'Top {top_n} Feature Importance (Mean over Folds)', fontsize=16)\n",
    "    plt.xlabel('Mean Importance', fontsize=12)\n",
    "    plt.ylabel('Feature', fontsize=12)\n",
    "    \n",
    "    # 添加数值标签\n",
    "    for i, v in enumerate(mean_importance['importance']):\n",
    "        ax.text(v + 0.005, i, f'{v:.3f}', color='black', va='center', fontsize=10)\n",
    "    \n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "1c32c2ed",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 使用示例（假设你已经运行了cv_model函数）\n",
    "plot_feature_importance(feat_importance, top_n=100)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
